@article{xi_patel_dong_que_qu_2018, title={Acetosyringone treatment duration affects large T-DNA molecule transfer to rice callus}, volume={18}, ISSN={["1472-6750"]}, DOI={10.1186/s12896-018-0459-5}, abstractNote={Large T-DNA fragment transfer has long been a problem for Agrobacterium-mediated transformation. Although vector systems, such as the BIBAC series, were successfully developed for the purpose, low transformation efficiencies were consistently observed. To gain insights of this problem in monocot transformation, we investigated the T-strand accumulation of various size of T-DNA in two kinds of binary vectors (one copy vs. multi-copy) upon acetosyringone (AS) induction and explored ways to improve the efficiency of the large T-DNA fragment transfer in Agrobacterium-mediated rice transformation. By performing immuno-precipitation of VirD2-T-strands and quantitative real-time PCR assays, we monitored the accumulation of the T-strands in Agrobacterium tumeficiens after AS induction. We further demonstrated that extension of AS induction time highly significantly improved large-size T-DNA transfer to rice cells. Our data provide valuable information of the T-strand dynamics and its impact on large T-DNA transfer in monocots, and likely dicots as well.}, journal={BMC BIOTECHNOLOGY}, author={Xi, Jing and Patel, Minesh and Dong, Shujie and Que, Qiudeng and Qu, Rongda}, year={2018}, month={Aug} }
 @article{xi_xie_yoshida_2017, title={Distributions of topological tree metrics between a species tree and a gene tree}, volume={69}, ISSN={["1572-9052"]}, DOI={10.1007/s10463-016-0557-x}, abstractNote={In order to conduct a statistical analysis on a given set of phylogenetic gene trees, we often use a distance measure between two trees. In a statistical distance-based method to analyze discordance between gene trees, it is a key to decide “biologically meaningful” and “statistically well-distributed” distance between trees. Thus, in this paper, we study the distributions of the three tree distance metrics: the edge difference, the path difference, and the precise K interval cospeciation distance, between two trees: First, we focus on distributions of the three tree distances between two random unrooted trees with n leaves ( $$n \ge 4$$ ); and then we focus on the distributions the three tree distances between a fixed rooted species tree with n leaves and a random gene tree with n leaves generated under the coalescent process with the given species tree. We show some theoretical results as well as simulation study on these distributions.}, number={3}, journal={ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS}, author={Xi, Jing and Xie, Jin and Yoshida, Ruriko}, year={2017}, month={Jun}, pages={647–671} }
 @article{davidson_rusinko_vernon_xi_2017, title={Modeling the distribution of distance data in Euclidean space}, volume={685}, ISBN={["978-1-4704-2321-6"]}, ISSN={["1098-3627"]}, DOI={10.1090/conm/685/13750}, abstractNote={Phylogenetic inference-the derivation of a hypothesis for the common evolutionary history of a group of species- is an active area of research at the intersection of biology, computer science, mathematics, and statistics. One assumes the data contains a phylogenetic signal that will be recovered with varying accuracy due to the quality of the method used, and the quality of the data. 
The input for distance-based inference methods is an element of a Euclidean space with coordinates indexed by the pairs of organisms. For several algorithms there exists a subdivision of this space into polyhedral cones such that inputs in the same cone return the same tree topology. The geometry of these cones has been used to analyze the inference algorithms. In this chapter, we model how input data points drawn from DNA sequences are distributed throughout Euclidean space in relation to the space of tree metrics, which in turn can also be described as a collection of polyhedral cones.}, journal={ALGEBRAIC AND GEOMETRIC METHODS IN DISCRETE MATHEMATICS}, author={Davidson, Ruth and Rusinko, Joseph and Vernon, Zoe and Xi, Jing}, year={2017}, pages={117–135} }
 @article{xi_yoshida_2015, title={THE CHARACTERISTIC IMSET POLYTOPE OF BAYESIAN NETWORKS WITH ORDERED NODES}, volume={29}, ISSN={["1095-7146"]}, DOI={10.1137/130933848}, abstractNote={In 2010, M. Studen\'y, R. Hemmecke, and S. Linder explored a new algebraic description of graphical models, called characteristic imsets. Compare with standard imsets, characteristic imsets have several advantages: they are still unique vector representative of conditional independence structures, they are 0-1 vectors, and they are more intuitive in terms of graphs than standard imsets. After defining a characteristic imset polytope (cim-polytope) as the convex hull of all characteristic imsets with a given set of nodes, they also showed that a model selection in graphical models, which maximizes a quality criterion, can be converted into a linear programming problem over the cim-polytope. However, in general, for a fixed set of nodes, the cim-polytope can have exponentially many vertices over an exponentially high dimension. Therefore, in this paper, we focus on the family of directed acyclic graphs (DAGs) whose nodes have a fixed order. This family includes diagnosis models which can be described by Bipartite graphs with a set of $m$ nodes and a set of $n$ nodes for any $m, n \in \Z_+$. In this paper, we first consider cim-polytopes for all diagnosis models and show that these polytopes are direct products of simplices. Then we give a combinatorial description of all edges and all facets of these polytopes. Finally, we generalize these results to the cim-polytopes for all Bayesian networks with a fixed underlying ordering of nodes with or without fixed (or forbidden) edges.}, number={2}, journal={SIAM JOURNAL ON DISCRETE MATHEMATICS}, author={Xi, Jing and Yoshida, Ruriko}, year={2015}, pages={697–715} }